Strong Gravitational Lens Modeling with Spatially Variant Point Spread Functions

TL;DR

This paper introduces Mirage, an iterative gravitational lens modeling tool that incorporates spatially variant point-spread functions, improving the accuracy of source reconstruction in lensing images.

Contribution

The paper presents a novel method to include spatially variant PSFs in gravitational lens modeling, enhancing the realism and precision of source reconstructions.

Findings

Successfully integrated spatially variant PSFs into lens modeling

Demonstrated improved accuracy in source reconstruction

Validated the method with simulated lensing data

Abstract

Astronomical instruments generally possess spatially variant point-spread functions, which determine the amount by which an image pixel is blurred as a function of position. Several techniques have been devised to handle this variability in the context of the standard image deconvolution problem. We have developed an iterative gravitational lens modeling code called Mirage that determines the parameters of pixelated source intensity distributions for a given lens model. We are able to include the effects of spatially variant point-spread functions using the iterative procedures in this lensing code. In this paper, we discuss the methods to include spatially variant blurring effects and test the results of the algorithm in the context of gravitational lens modeling problems.